Abstract
A tuning procedure for a model predictive controller (MPC) is presented for multi-input multi-output systems. The approach consists of two steps based on a hybrid method: the goal attainment method and a variable neighborhood search. In the first step, the weights of the MPC objective function are obtained, minimizing the square error between the closed-loop response of the internal controller model and a predefined desired reference trajectory. In the second step, the integer variables of the problem (prediction and control horizons) are obtained, minimizing the square error between the closed-loop response and an optimal trajectory, aiming a controller with low computational cost and good performance. The proposed method was tested in two benchmark processes using different MPC formulations, showing satisfactory results.
Funder
Coordenação de Aperfeicoamento de Pessoal de Nível Superior
National Council for Scientific and Technological Development
Subject
Process Chemistry and Technology,Chemical Engineering (miscellaneous),Bioengineering
Cited by
5 articles.
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